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P2 IntelliTopo: An IaC Generation Service for Industrial Network Topology Construction

IntelliTopo:面向工业网络拓扑构建的 IaC 生成服务
ASE 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)2025匹配度 3/10 · 论文将 LLM 用于工业网络 IaC 生成,涉及 PL/DSL 与工业落地,但与用户核心方向(静态分析/形式化验证、浮点程序分析、贝叶斯程序分析及其与 LLM 的交叉)无直接关联;它更接近配置代码生成而非程序分析。引用 2 inbox
Mingyu Shao, Zhao Liu, Weihong Han, Cuiyun Gao, Jiachen Liu, Qing Liao
crossref: 2026-09-12

AI 速览

一句话:提出首个面向工业网络拓扑构建的 IaC 生成框架,通过语义拓扑解析与领域感知镜像检索增强 LLM,将部署时间从天缩短到小时。

工业网络仿真中的拓扑构建需根据自然语言需求设计设备结构布局与配置规则,而 IaC 可用机器可读代码管理设备。现有 LLM 驱动的 IaC 生成方法只生成孤立配置,忽视整体拓扑,且因缺乏行业设备镜像知识而难以适配多种行业场景。IntelliTopo 是首个面向工业网络拓扑构建的 IaC 生成框架,通过语义拓扑解析增强 LLM 对整体拓扑结构的理解,并通过领域感知镜像检索使输出更贴合真实工业场景。该系统部署于 PaaS 平台并连续运行 3 个月,处理 10 多个行业的 50 多个网络仿真任务,将平均拓扑部署时间从数天降至数小时,同时降低 LLM 推理算力需求,弥合高层需求与可执行基础设施之间的鸿沟。

问题
现有 LLM 驱动的 IaC 生成方法只关注孤立设备配置,缺乏对整体网络拓扑结构的建模,且难以适配行业专用设备镜像。
方法
IntelliTopo 通过语义拓扑解析增强 LLM 对整体拓扑结构的理解,并通过领域感知镜像检索使生成结果更符合真实工业场景。
评估
系统部署于 PaaS 平台并连续运行 3 个月,处理 10 多个行业的 50 多个网络仿真任务,验证了平均部署时间从数天降至数小时且降低 LLM 推理算力需求。
原文摘要(Abstract)

Network topology construction in this paper refers to designing the structural layouts and configuration rules among network devices according to natural language requirements in network simulation. Relatedly, Infrastructure as Code (IaC) enables the configuration and management of network devices through machine-readable code. Although there exist IaC generation approaches powered by Large Language Models (LLMs), they only focus on generating isolated configurations without consideration for holistic topology structure, leading to failure to form a complete, functional topology. Additionally, due to the LLMs’ limited knowledge of industry-specific device images, existing approaches struggle to adapt to diverse industry scenarios.In this paper, we introduce IntelliTopo, which, to the best of our knowledge, is the first IaC generation framework targeted at industrial network topology construction. Specifically, IntelliTopo enhances the capabilities of LLMs through two novel mechanisms: (1) Through semantic topology parsing, we enhance the LLMs’ understanding of the holistic topology structure; (2) Through domain-aware image retrieval, the outputs of IntelliTopo are more aligned with real-world industry scenarios. Deployed on our PaaS system, the IntelliTopo service has operated continuously for 3 months, handling 50+ network simulation tasks across 10+ industries. IntelliTopo reduces average network topology deployment time from days to hours while requiring less computational power for LLM reasoning. This work bridges the gap between high-level requirements and executable infrastructure, providing a scalable solution for network topology construction.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot9283,
  title = {IntelliTopo: An IaC Generation Service for Industrial Network Topology Construction},
  author = {Mingyu Shao and Zhao Liu and Weihong Han and Cuiyun Gao and Jiachen Liu and Qing Liao},
  booktitle = {ASE},
  year = {2025},
  doi = {10.1109/ase63991.2025.00298}
}